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Screening of ulcerative colitis biomarkers and potential pathways based on weighted gene co-expression network, machine learning and ceRNA hypothesis

Overview of attention for article published in Hereditas, November 2022
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Title
Screening of ulcerative colitis biomarkers and potential pathways based on weighted gene co-expression network, machine learning and ceRNA hypothesis
Published in
Hereditas, November 2022
DOI 10.1186/s41065-022-00259-4
Pubmed ID
Authors

Ying Li, Mengyao Tang, Feng Jun Zhang, Yihan Huang, Jing Zhang, Junqi Li, Yunpeng Wang, Jinguang Yang, Shu Zhu

Abstract

Ulcerative colitis (UC) refers to an intractable intestinal inflammatory disease. Its increasing incidence rate imposes a huge burden on patients and society. The UC etiology has not been determined, so screening potential biomarkers is critical to preventing disease progression and selecting optimal therapeutic strategies more effectively. The microarray datasets of intestinal mucosal biopsy of UC patients were selected from the GEO database, and integrated with R language to screen differentially expressed genes and draw proteins interaction network diagrams. GO, KEGG, DO and GSEA enrichment analyses were performed to explore their biological functions. Through machine learning and WGCNA analysis, targets that can be used as UC potential biomarkers are screened out. ROC curves were drawn to verify the reliability of the results and predicted the mechanism of marker genes from the aspects of immune cell infiltration, co-expression analysis, and competitive endogenous network (ceRNA). Two datasets GSE75214 and GSE87466 were integrated for screening, and a total of 107 differentially expressed genes were obtained. They were mainly related to biological functions such as humoral immune response and inflammatory response. Further screened out five marker genes, and found that they were associated with M0 macrophages, quiescent mast cells, M2 macrophages, and activated NK cells in terms of immune cell infiltration. The co-expression network found significant co-expression relationships between 54 miRNAs and 5 marker genes. According to the ceRNA hypothesis, NEAT1-miR-342-3p/miR-650-SLC6A14, NEAT1-miR-650-IRAK3, and XIST-miR-342-3p-IRAK3 axes were found as potential regulatory pathways in UC. This study screened out five biomarkers that can be used for the diagnosis and treatment of UC, namely SLC6A14, TIMP1, IRAK3, HMGCS2, and APOBEC3B. Confirmed that they play a role in the occurrence and development of UC at the level of immune infiltration, and proposed a potential RNA regulatory pathway that controls the progression of UC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 14%
Student > Master 1 14%
Unknown 5 71%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 14%
Unknown 6 86%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 November 2022.
All research outputs
#22,778,604
of 25,392,582 outputs
Outputs from Hereditas
#444
of 513 outputs
Outputs of similar age
#416,325
of 487,704 outputs
Outputs of similar age from Hereditas
#4
of 5 outputs
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